In order to determine damage to an anatomical joint, it is common in medical practice today to use imaging techniques to depict the anatomical joint of interest and further to have a medical expert analyze the captured image data to determine whether there is damage. The medical expert then makes annotations about the conclusions drawn from the analysis of image data. The annotations are made available to a surgeon or orthopedic staff member who uses the annotations and the captured image data as a decision support for diagnosis and decision of suitable treatment of the patient.
However, this process is not very efficient as a manner of providing decision support, as only a fraction of the information that the medical expert in this way gathers when analyzing the image data, based on the knowledge of the medical expert, can be communicated in the present annotation format. Therefore, the decision support material received by the surgeon or orthopedic staff member is often inadequate.
Pierre Dodin et al: “A fully automated system for quantification of knee bone marrow lesions using MRI and the osteoarthritis initiative cohort”, Journal of Biomedical Graphics and Computing, 2013, Vol. 3, No. 1, 20 Nov. 2012 describes an automated BML quantification method.
WO 2015/117663 describes a method of manufacturing a surgical kit for cartilage repair in an articulating surface of a joint in which a three dimensional image representation of a surface of the joint is generated.